Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular
both with clinicians and researchers as they are capable of providing unique insights into …

To increase granularity in human neuroimaging science, we designed and built a next-
generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by …

Abstract Magnetic Resonance Imaging (MRI) is an essential technology in modern
medicine. However, one of its main drawbacks is the long scan time needed to localize the …

We present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic
resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single …

Limited detection power has been a bottleneck for subject-specific functional MRI (fMRI)
studies; however, the higher signal-to-noise ratio afforded by ultra-high magnetic fields (≥ 7 …

Purpose A segmented k‐space blipped‐controlled aliasing in parallel imaging (skipped‐
CAIPI) sampling strategy for EPI is proposed, which allows for a flexible choice of EPI factor …

Purpose To introduce a combined machine learning (ML)‐and physics‐based image
reconstruction framework that enables navigator‐free, highly accelerated multishot echo …

Structured low-rank matrix models have previously been introduced to enable
calibrationless MR image reconstruction from sub-Nyquist data, and such ideas have …

Purpose To alleviate the spatial encoding limitations of single‐shot echo‐planar imaging
(EPI) by developing multi‐shot segmented EPI for ultra‐high‐resolution functional MRI …